10 citations · 18 across the 5 of their papers we have counts for
5 papers
When Can Test-Time Adaptation Help Zero-Shot CT Vision-Language Models?
Ailar Mahdizadeh, Puria Azadi Moghadam, Xiangteng He +1
3D CT vision-language models (VLMs) classify abnormalities from text prompts in a zero-shot manner, enabling cross-institution deployment where labels are scarce and clinical tasks…
SCALE-VLP: Soft-Weighted Contrastive Volumetric Vision-Language Pre-training with Spatial-Knowledge Semantics
Ailar Mahdizadeh, Puria Azadi Moghadam, Xiangteng He +3
Vision-language models (VLMs) have demonstrated strong cross-modal capabilities, yet most work remains limited to 2D data and assumes binary supervision (i.e., positive vs. negativ…
AMIGO: Sparse Multi-Modal Graph Transformer with Shared-Context Processing for Representation Learning of Giga-pixel Images
Ramin Nakhli, Puria Azadi Moghadam, Haoyang Mi +4
Processing giga-pixel whole slide histopathology images (WSI) is a computationally expensive task. Multiple instance learning (MIL) has become the conventional approach to process…
A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images
Puria Azadi Moghadam, Sanne Van Dalen, Karina C. Martin +4
Visual microscopic study of diseased tissue by pathologists has been the cornerstone for cancer diagnosis and prognostication for more than a century. Recently, deep learning metho…
Deep Q-Learning for Dynamic Reliability Aware NFV-Based Service Provisioning
Hamed Rahmani Khezri, Puria Azadi Moghadam, Mohammad Karimzadeh Farshbafan +3
Network function virtualization (NFV) is referred to the technology in which softwarized network functions virtually run on commodity servers. Such functions are called virtual net…